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Genomic Analysis of Stropharia rugosoannulata Reveals Its Nutritional Strategy and Application Potential in Bioremediation

Stropharia rugosoannulata is not only a popular edible mushroom, but also has excellent potential in bioremediation. In this study, we present a high-quality genome of a monokaryotic strain of the S. rugosoannulata commercial cultivar in China. The assembly yielded an N50 length of 2.96 Mb and a total size of approximately 48.33 Mb, encoding 11,750 proteins. The number of heme peroxidase-encoding genes in the genome of S. rugosoannulata was twice the average of all of the tested Agaricales. The genes encoding lignin and xenobiotic degradation enzymes accounted for more than half of the genes encoding plant cell wall degradation enzymes. The expansion of genes encoding lignin and xenobiotic degradation enzymes, and cytochrome P450 involved in the xenobiotic metabolism, were responsible for its strong bioremediation and lignin degradation abilities. S. rugosoannulata was classified as a litter-decomposing (LD) fungus, based on the analysis of the cell wall degrading enzymes. Substrate selection for fruiting body cultivation should consider both the nutritional strategy of LD and a strong lignin degradation ability. Consistent with safe usage as an edible mushroom, the S. rugosoannulata genome does not contain genes for known psilocybin biosynthesis. Genome analysis will be helpful for understanding its nutritional strategy to guide fruiting body cultivation and for providing insight into its application in bioremediation.

Introduction
Stropharia rugosoannulata Farl. Ex Murrill, called saketsubatake in Japanese and winecap Stropharia in English, is a popular edible mushroom with high nutritional and medicinal values. S. rugosoannulata was first domesticated in Germany in the 1960s [1] and was recommended by the Food and Agriculture Organization as a cultivated mushroom for developing countries [2]. By 1989, commercial production of Stropharia in Europe reached approximately 1300 tons per year [3]. Field cultivation of S. rugosoannulata has expanded in most of the provinces in China, and the cultivation area was estimated to be approximately 1333 ha in 2019.
In recent years, the consumption of S. rugosoannulata has increased dramatically due to its excellent taste and pharmacological activities. In addition to its nutritional and medicinal values [4,5], S. rugosoannulata has great potential for bioremediation. It can degrade a wide range of structurally different environmental pollutants, including polycyclic aromatic hydrocarbons [6], synthetic dyes [7], 2,4,6-trinitrotoluene [8], bisphenol A [9], and dibenzo-p-dioxins and dibenzofurans [10], as well as pharmaceutical compounds such as carbamazepine, venlafaxine, iopromide, diclofenac, cyclophosphamide, and ifosfamide [11]. S. rugosoannulata has been found to be a promising fungal species

Origin of the Strain, Culture Conditions, and DNA/RNA Preparation
The strain "Heinong No. 1" (CGMCC 5.2220) is a culture of commercial cultivar of S. rugosoannulata in China. The monokaryotic strain was obtained as follows: First, the fruiting bodies of strain "Heinong No. 1" were cultivated, and basidiospores were collected. Then, the basidiospores were sprayed on potato dextrose agar (PDA) and incubated at 25 • C for 10 days until spore germination. Thereafter, single spore isolates without any clamp connection were selected under 600× magnification using an optical microscope (Eclipse 80i, Nikon, Tokyo, Japan) and were subcultured individually on PDA plates at 25 • C (Figure 1). connection were selected under 600× magnification using an optical microscope (Eclipse 80i, Nikon, Tokyo, Japan) and were subcultured individually on PDA plates at 25 °C (Figure 1). A vegetative monokaryotic strain S68 derived from the "Heinong No. 1" strain was cultured in potato dextrose broth (PDB) at 25 °C and 150 rpm for 7 days. Mycelia were harvested by filtering and being ground in liquid nitrogen. High-quality genomic DNA was then extracted using the QIAGEN ® Genomic kit (Qiagen, Dusseldorf, Germany) following the manufacturer's instructions. Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA).

Library Construction, Genome/Transcriptome Sequencing, and Assembly
The Illumina HiSeq X-Ten and PacBio SEQUEL platforms were used for genome sequencing at Nextomics Biosciences Co., Ltd. (Nextomics Biosciences, Wuhan, China). A 350-bp library was constructed following Illumina's standard protocol, and it was subjected to paired-ended 150-bp sequencing by Illumina HiSeq X-ten. The sequencing data (clean bases: 6.52G, ~129X coverage of the estimated genome size; Table S1) were used to estimate the genome size, repeat content, and heterozygosity.
Then, a 20-kb library was constructed following PacBio's standard methods. The library was quantified using NanoDrop (Thermo Scientific, Waltham, MA, USA) and Qubit (Invitrogen, Carlsbad, CA, USA), and then sequenced through single-molecule real-time (SMRT) sequencing (PacBio Sequel, PacBio, Menlo Park, CA, USA). The sequencing data (filtered reads: 14.56 G, ~266X coverage of the estimated genome size; Table S1) were assembled using Falcon (v1.8.1) with the default parameters. The completeness of the assembled genome was evaluated using the Core Eukaryotic Genes Mapping Approach (CEGMA) v2 and Benchmarking Universal Single-Copy Orthologs (BUSCO v 4.0.5) with conserved orthologous gene profiles for fungi.
For the transcriptome analysis, the strain "Heinong No. 1" was cultured on PDA media and the mycelia were collected for RNA extraction. Three libraries were generated using the NEB Next Ultra RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA) A vegetative monokaryotic strain S68 derived from the "Heinong No. 1" strain was cultured in potato dextrose broth (PDB) at 25 • C and 150 rpm for 7 days. Mycelia were harvested by filtering and being ground in liquid nitrogen. High-quality genomic DNA was then extracted using the QIAGEN ® Genomic kit (Qiagen, Dusseldorf, Germany) following the manufacturer's instructions. Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA).

Library Construction, Genome/Transcriptome Sequencing, and Assembly
The Illumina HiSeq X-Ten and PacBio SEQUEL platforms were used for genome sequencing at Nextomics Biosciences Co., Ltd. (Nextomics Biosciences, Wuhan, China). A 350-bp library was constructed following Illumina's standard protocol, and it was subjected to paired-ended 150-bp sequencing by Illumina HiSeq X-ten. The sequencing data (clean bases: 6.52G,~129X coverage of the estimated genome size; Table S1) were used to estimate the genome size, repeat content, and heterozygosity.
Then, a 20-kb library was constructed following PacBio's standard methods. The library was quantified using NanoDrop (Thermo Scientific, Waltham, MA, USA) and Qubit (Invitrogen, Carlsbad, CA, USA), and then sequenced through single-molecule real-time (SMRT) sequencing (PacBio Sequel, PacBio, Menlo Park, CA, USA). The sequencing data (filtered reads: 14.56 G,~266X coverage of the estimated genome size; Table S1) were assembled using Falcon (v1.8.1) with the default parameters. The completeness of the assembled genome was evaluated using the Core Eukaryotic Genes Mapping Approach (CEGMA) v2 and Benchmarking Universal Single-Copy Orthologs (BUSCO v 4.0.5) with conserved orthologous gene profiles for fungi.
For the transcriptome analysis, the strain "Heinong No. 1" was cultured on PDA media and the mycelia were collected for RNA extraction. Three libraries were generated using the NEB Next Ultra RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA) and were sequenced on an Illumina HiSeq X-ten platform (Illumina Inc., San Diego, CA, USA) by Nextomics Biosciences Co., Ltd. (Wuhan, China).

Repeat Annotation, Gene Prediction, Gene Function, and Noncoding RNA Annotation
Tandem repeats were identified using GMATA V2.2 [26]. For the transposable element (TE), ab initio prediction was performed using RepeatModeler version open-1.0.11 to establish a de novo repeat sequence library, which was then classified by TEclass [27]. Finally, RepeatMasker Revision 1.331 was used to search against the de novo repeat sequence database generated from RepeatModeler's prediction.
The predicted genes of S. rugosoannulata were annotated by alignment against the non-redundant Protein Database in National Center for Biotechnology Information (NCBI), Kyoto Encyclopedia of Gene and Genomes (KEGG), Eukaryotic Orthologous Groups of protein (KOG), Gene Ontology (GO), and SwissProt databases. Furthermore, motifs and domains were annotated using InterPro scan 5.32-71.0.
Non-coding RNAs, including rRNAs, snRNAs, microRNAs, and tRNAs, were identified by adopting infernal v1.1.2 using the Rfam database [31] for the S. rugosoannulata genome using BLASTN (E-value ≤ 1e −5 ). Transfer RNA was predicted using tRNAs can-SE v2.0 software with the default parameters for eukaryotes. The rRNAs and their subunits were predicted using RNAmmer v1.2. Protein targeting predictions were made using SignalP and TMHMM.
Furthermore, the genome completeness of the assembly was evaluated by BUSCO, RNA-seq data, and comparative analysis with the genomes of closely related genetic species.
2.6. Classification of the Nutritional Strategy of S. rugosoannulata by Linear Discriminant Analysis (LDA) Based on the PCWD Gene Families LDA is used in statistics and other fields to find a linear combination of features that characterize or separate two or more classes of objects or events [40]. Forty-four PCWD gene families that were sorted into three functional categories, namely, cellulose, hemicellulose (including pectin), and lignin/xenobiotic degradation [25], were identified in the genome of S. rugosoannulata according to the Pfam, Interpro, and SSF identifiers. The nutritional strategy of S. rugosoannulata was determined by LDA with SPSS version 25.0 (IBM Corporation, Armonk, NY, USA) using the protein dataset for these 44 PCWD gene families of three different nutritional strategies (BR, WR, and LD) [25].

Sequencing Output Processing and De Novo Genome Assembly
The S. rugosoannulata genome was sequenced by both the Illumina and PacBio SMRT platforms. Subread distribution analyses confirmed the high quality of the 20-kb library ( Figure S1). There was no apparent heterozygous peak, and the heterozygosity was low at 0.01% ( Figure S2). The resulting assembly yielded 48.33 Mb from~266X coverage (Table 1), comprising 21 scaffolds with 100% of the genome assembled in the scaffolds exceeding 5 kb in length (Table S3 and Figure 2). Telomeres were identified manually by sequence observation, and all were TTTAGGG repeats of approximately 100 bp in length. Two contigs with telomeric repeats on both ends were found, and 14 of these scaffolds contained characteristic (TTTAGGG)n telomeric repeats on either the 5 or 3 end (Table S4). The N50 and N90 lengths were 2.96 and 1.35 Mb, respectively (Table 1). A total of 94.59% of the 758 BUSCO genes and 96.77% of the 248 core genes by CEGMA were completely detected in the genome, indicating the completeness of the assembled genome ( Figure S3). The previous assembly of S. rugosoannulata strain MG69 had 17,725 contigs with an N50 of only 8.32 kbp, and BUSCO was only 87.60% (Table S5) [20].

Gene Prediction and Genome-Wide Functional Annotation
The prediction of TEs and other repetitive DNA sequences for the S. rugosoannulata genome identified that these regions comprised approximately 9.62 Mb or 19.91% of the genome, with TE accounting for 17.48% (Table 2 and Figure 2). Among the 16 tested species of Agaricomycetes, the proportion of repetitive sequences in the S. rugosoannulata genome was higher than most of the species (Figure 3).

Gene Prediction and Genome-Wide Functional Annotation
The prediction of TEs and other repetitive DNA sequences for the S. rugosoannulata genome identified that these regions comprised approximately 9.62 Mb or 19.91% of the genome, with TE accounting for 17.48% (Table 2 and Figure 2). Among the 16 tested species of Agaricomycetes, the proportion of repetitive sequences in the S. rugosoannulata genome was higher than most of the species (Figure 3).
The most abundant transposable and repetitive element types were Class I long terminal repeats (LTRs) with 5.39 Mb (11.15%), Class II DNA transposon with 1.75 Mb (3.61%), and long interspersed nuclear element (LINE) with 0.79 Mb (1.64%). Approximately 0.47% of the S. rugosoannulata genome was identified as tandem repeats, and a total of 22,553 SSRs were identified (Table 2).
To increase the accuracy, we used multiple tools to predict the gene structure and function (Table S6). The final integration led to a dataset containing 11,750 protein-coding gene models with an average gene sequence length of 1942 bp, giving rise to a gene density of 47.21% in the assembled 48,331,048 bp. Among the 11,750 gene models, the average CDS length was 1455.07 bp, with an average exon number of 6.25 and 232.84 bp (Table 1).   The most abundant transposable and repetitive element types were Class I long terminal repeats (LTRs) with 5.39 Mb (11.15%), Class II DNA transposon with 1.75 Mb (3.61%), and long interspersed nuclear element (LINE) with 0.79 Mb (1.64%). Approximately 0.47% of the S. rugosoannulata genome was identified as tandem repeats, and a total of 22,553 SSRs were identified (Table 2).
To increase the accuracy, we used multiple tools to predict the gene structure and function (Table S6). The final integration led to a dataset containing 11,750 protein-coding gene models with an average gene sequence length of 1942 bp, giving rise to a gene For the non-coding gene, the rRNA cluster was found on scaffold 8 of the assembly, and the genes of 5.8S-18S-28S clustered in a region of 19 kb. There were 197 predicted tRNA genes, corresponding to 0.036% of the genome assembly length.
A total of 11,377 genes (96.83%) were annotated using the functional databases (GO, KEGG, KOG, SwissProt, and Nr) (Table S6). According to the GO database, 5496 annotated genes were assigned to GO categories, with the first five as "metabolic process", "binding", "catalytic activity", "cellular process", and "single-organism process" ( Figure S4). By mapping to the KEGG database, "Global and overview maps" accounted for the majority of the KEGG annotations, with 994 (25.98%) proteins classified into these categories ( Figure S5). Other highly represented pathways were "signal transduction" with 330 (8.63%) and "transport and catabolism" with 320 (8.36%).

Phylogenomic Analyses
The whole-genome sequences of 15 species of Agaricales were used for phylogenomic analysis (Table S2). The species of G. frondosa (Polyporales) was included as an outgroup. The clustering of proteomes resulted in 8341 groups in the S. rugosoannulata genome, of which 1609 were core single-copy orthologous genes among 15 fungi, and 377 were unique gene families in S. rugosoannulata (Table S8 and Figure S6).
A maximum likelihood (ML) phylogeny analysis for S. rugosoannulata and the 15 additional fungal species was performed based on 1609 shared single-copy orthologous genes, which were concatenated into a supermatrix with 584, 537 amino acid sites (Figure 2a). Three clades of Agaricales, Agaricoid, Tricholomatoid, and Marasmioid [42] were significantly supported with high bootstrap values. S. rugosoannulata is phylogenetically close to H. sublateritium and P. highlandensis (Figure 2a). They all belong to Strophariaceae. The whole-genome sequences of S. rugosoannulata CGMCC 5.2220 and H. sublateritium FD-334 SS-4 showed a high level of sequence collinearity ( Figure S7).

Putative Peroxidase-Encoding Genes in the Genome of S. rugosoannulata
Peroxidases can be divided into two significant groups contingent upon a heme cofactor's presence or absence [38]. The S. rugosoannulata genome contains 50 heme peroxidases, 10 non-heme peroxidases, and one NADPH oxidase regulator (Table S9). Putative peroxidase-encoding genes of all 63 Agricomycotina fungi recorded in fPoxDB (accessed on 20 December 2020), including biotrophs (ectomycorrhizal, mycoparasite, and root endophyte), BR and WR fungi, were retrieved and compared (Table S9). There was an average of 34.7 peroxidase-encoding genes in the genome of these Agaricomycete fungi. Sixty-one peroxidase-encoding genes were identified in S. rugosoannulata, much more than the majority of the tested Agaricomycete fungi. Among the 61 peroxidase-encoding genes, there were 50 genes encoding heme peroxidases in S. rugosoannulata, twice the average (25) of all of the tested fungi.
Phylogenetic trees were constructed based on the predicted amino acid sequences of the heme peroxidases and non-heme peroxidases of S. rugosoannulata, respectively, and the transcription levels were analyzed ( Figure 4A,B). Among the 50 heme peroxidases, the proteins belonging to the same family generally were grouped together, including manganese peroxidase, hybrid ascorbate-cytochrome c peroxidases (also named hybridtype A peroxidases, APx-CcPs), heme-thiolate peroxidases (HTPs), linoleate diol synthase, and NADPH oxidase genes (Nox). The relationships between peroxidase families were relatively weak, as indicated by the low bootstrap values ( Figure 4A).

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A peroxidases, APx-CcPs), heme-thiolate peroxidases (HTPs), linoleate diol synthase, and NADPH oxidase genes (Nox). The relationships between peroxidase families were relatively weak, as indicated by the low bootstrap values ( Figure 4A).  Four main groups of fungal class II peroxidases were classified by Floudas et al. [44] based on structure-functional properties: lignin peroxidase (LiP; EC 1.11.1.14), manganese peroxidase (MnP; EC 1.11.1.13), versatile peroxidase (VP; EC 1.11.1.16), and generic peroxidases (GP; EC 1.11.1.7). Seventeen putative MnP-encoding genes were identified in the genome of S. rugosoannulata and there were no genes encoding GP, LiP and VP. MnP proteins are defined as possessing an Mn (II)-oxidation site near the internal propionate of heme formed by three acidic residues referred to as Phanerochaete chrysosporium MnP1 Glu35, Glu39, and Asp179 and Pleurotus eryngii VPL Glu36, Glu40, and Asp175 [44]. The average number of MnP-encoding genes per species was only five in the 62 tested Four main groups of fungal class II peroxidases were classified by Floudas et al. [44] based on structure-functional properties: lignin peroxidase (LiP; EC 1.11.1.14), manganese peroxidase (MnP; EC 1.11.1.13), versatile peroxidase (VP; EC 1.11.1.16), and generic peroxidases (GP; EC 1.11.1.7). Seventeen putative MnP-encoding genes were identified in the genome of S. rugosoannulata and there were no genes encoding GP, LiP and VP. MnP proteins are defined as possessing an Mn (II)-oxidation site near the internal propionate of heme formed by three acidic residues referred to as Phanerochaete chrysosporium MnP1 Glu35, Glu39, and Asp179 and Pleurotus eryngii VPL Glu36, Glu40, and Asp175 [44]. The average number of MnP-encoding genes per species was only five in the 62 tested Agaricomycete fungi; however, there were 17 MnP-encoding genes in the genome of S. rugosoannulata. All 17 MnP proteins were atypical, with only two acidic residues at the Mn-oxidation site (Table S10). It has been reported that 14 MnP genes in the genome of H. sublateritium are atypical [28]. The majority of MnPs were secreted proteins, and 13 of the 17 MnP genes were expressed in the mycelia of S. rugosoannulata (Table S11 and Figure 4A).
APx-CcPs share the enzymatic and structural features of ascorbate and cytochrome c peroxidases. Almost no Apx-CcP was found in most of the ectomycorrhizal and BR fungi. There was an average of one gene encoding APx-CcP in the genome of 62 tested Agaricomycete fungi (Table S9); however, 10 were detected in the genome of S. rugosoannulata. H. sublateritium, the species in the same family of S. rugosoannulata, had 7 APx-CcP genes. Ten and eight genes were detected in the species Galerina marginata and Gymnopus luxurians, respectively. We then performed a phylogenetic analysis of the APx-CcP proteins from these four species. Generally, APx-CcP proteins from G. marginata and G. luxurians were clustered as a group, and those from S. rugosoannulata and H. sublateritium were clustered together ( Figure 4C). All 10 APx-CcPs were secreted proteins, and SRUG_02817 showed the top three highest expression levels among all the peroxidase-encoding genes (Table S11 and Figure 4A).
Dye-decolorizing peroxidases (DyPs; EC 1.11.1.19) are a newly discovered family of heme peroxidases unrelated to well-known peroxidases in terms of their amino acid sequences, tertiary structures, and catalytic residues [45]. One gene encoding DyP was identified in the genome of S. rugosoannulata. DyP-encoding genes are widespread among WR genomes but are absent from the majority of BR genomes (Table S9).

The Nutritional Strategy of S. rugosoannulata
A total of 371 genes could be assigned to CAZyme families, as defined in the CAZy database (Table S12), which consisted of 165 genes encoding glycoside hydrolases (GHs), 107 auxiliary activity families (AAs), 55 glycosyltransferases (GTs), 25 carbohydrate esterase (CEs), 10 polysaccharide lyase (PLs), and 9 carbohydrate-binding modules (CBMs). Most of the Agaricales fungi that we have tested followed similar trends.
The terms WR, BR, and LD have traditionally been used to separate saprotrophic mushroom-forming fungi based on their nutritional strategies. Comparison of the genes associated with PCWD has revealed that LDs are significantly different from BR fungi, whereas LDs and WR fungi show both similarities and differences with respect to the composition of PCWD genes [25]. We then compared the genes encoding PCWD in S. rugosoannulata with LD, WR, and BR fungi. According to the previous research of Floudas et al., the genes encoding PCWD were divided into three functional groups: gene families encoding the enzymatic degradation of cellulose (12 families), hemicellulose (including pectin; 23 families), and lignin/xenobiotic (9 families) (Table S13). For S. rugosoannulata, BR can be ruled out by a preliminary comparison of PCWD-encoding genes ( Figure S8). It is difficult to determine whether S. rugosoannulata is an LD or WR fungus by direct analysis. Therefore, the nutritional strategy was analyzed by LDA analysis based on the 44 PCWD enzymes. Thirty-seven species from three groups (BR, LD, and WR) were examined. Ten characters with very low tolerance were excluded from the Failing Tolerance Test (default tolerance level 0.001) (Table S14-1). The remaining 34 of the 44 characters were included in the analysis and grouped correctly at a rate of 100% (Table S14-2). S. rugosoannulata was classified as an LD with 100% probability (Table S14).

Detection of Secondary Metabolite Clusters
A total of 34 gene clusters located on different scaffolds were predicted using Antismash, including 1 nonribosomal peptide synthase (NRPS) and 11 NRPS-like gene clusters, 1 type 1 polyketide synthase (T1PKS), 16 terpene synthases (TSs), 2 siderophores, and 3 indole clusters (Table S15 and Figure S9). The number of secondary metabolite clusters in the genome of S. rugosoannulata was much greater than that of commercially cultivated mushrooms A. bisporus, Lentinula edodes, and P. eryngii, which suggests that diverse secondary metabolites can be produced by S. rugosoannulata (Table S16).
Most fungi have no or only one siderophore cluster (Table S16); however, two siderophore clusters have been identified in the genome of S. rugosoannulata ( Figure 5A). Further analysis found that two core biosynthetic genes encoding siderophores in the majority of fungi, such as H. sublateritium and Coprinopsis cinerea, were adjacent and presented as a cluster ( Figure 5B). In S. rugosoannulata, the related orthologous core biosynthetic genes for siderophores are located on scaffolds 2 and 4, so two siderophore clusters were identified ( Figure 5B). Transcriptome analysis showed that all of the genes in the two siderophore clusters were expressed in the mycelia. were included in the analysis and grouped correctly at a rate of 100% (Table S14-2). S. rugosoannulata was classified as an LD with 100% probability (Table S14).

Detection of Secondary Metabolite Clusters
A total of 34 gene clusters located on different scaffolds were predicted using Antismash, including 1 nonribosomal peptide synthase (NRPS) and 11 NRPS-like gene clusters, 1 type 1 polyketide synthase (T1PKS), 16 terpene synthases (TSs), 2 siderophores, and 3 indole clusters (Table S15 and Figure S9). The number of secondary metabolite clusters in the genome of S. rugosoannulata was much greater than that of commercially cultivated mushrooms A. bisporus, Lentinula edodes, and P. eryngii, which suggests that diverse secondary metabolites can be produced by S. rugosoannulata (Table S16).
Most fungi have no or only one siderophore cluster (Table S16); however, two siderophore clusters have been identified in the genome of S. rugosoannulata ( Figure 5A). Further analysis found that two core biosynthetic genes encoding siderophores in the majority of fungi, such as H. sublateritium and Coprinopsis cinerea, were adjacent and presented as a cluster ( Figure 5B). In S. rugosoannulata, the related orthologous core biosynthetic genes for siderophores are located on scaffolds 2 and 4, so two siderophore clusters were identified ( Figure 5B). Transcriptome analysis showed that all of the genes in the two siderophore clusters were expressed in the mycelia.  It was recently confirmed that the NRPS gene cluster is responsible for produci coprinoferrin in the Basidiomycete C. cinerea [46]. This gene cluster includes 17 genes the genome of C. cinerea, and it was found that the 15 genes of the NRPS cluster (cluste in Figure S9) in S. rugosoannulata shared a sequence similarity of over 40% to 80% w those of C. cinerea ( Figure 5C and Table S17) and H. sublateritium, respectively, and the fore might be responsible for the production of coprinoferrin-related compounds. Tra scriptome analysis showed that all of the genes in the cluster were highly or moderat expressed.
Three indole clusters were found in the genome of S. rugosoannulata, far more th the majority of fungi that have no or only one indole cluster (Table S16). However, three core genes (SRUG_09987, SRUG_10137, and SRUG_11196) had no or very low pression in the mycelial sample.

No Genes Encoding Psilocybin Biosynthesis Enzymes Were Predicted in the Genome of S. rugosoannulata
The species of the genera Conocybe, Gymnopilus, Panaeolus, Pluteus, Psilocybe, and St pharia have been reported to be hallucinogenic mushrooms that contain psilocybin [47,4 Among the species of the genus Stropharia, S. coronilla has been reported to produ psilocin/psilocybin [49], and no psilocin/psilocybin was detected in S. rugosoannulata high-performance liquid chromatography (HPLC) analysis [50]. Enzymatic synthesis psilocybin has been reported in the phylogenetically closed species P. cubensis and P. c nescens [29]. We searched the genes encoding three key psilocybin biosynthesis enzym namely, tryptophan decarboxylase (PsiD), psilocybin-related N-methyltransferase (PsiM and psilocybin-related phosphotransferase (PsiK), in the genome of S. rugosoannulata was found that the proteins SRUG_10179, SRUG_02421, and SRUG_10672 have on 38.5%, 27.5%, and 44.4% identity with the related enzymes responsible for psilocybin b synthesis in P. cubensis, respectively. Phylogenetic analysis showed that the known psi cybin biosynthesis enzymes were grouped as a cluster with high support values, and related proteins of S. rugosoannulata are grouped into different clusters with PsiD, Ps and PsiM, which were confirmed to encode for psilocybin biosynthesis enzymes (Figu 6). This suggests that the gene cluster for psilocybin biosynthesis is absent in It was recently confirmed that the NRPS gene cluster is responsible for producing coprinoferrin in the Basidiomycete C. cinerea [46]. This gene cluster includes 17 genes in the genome of C. cinerea, and it was found that the 15 genes of the NRPS cluster (cluster 6 in Figure S9) in S. rugosoannulata shared a sequence similarity of over 40% to 80% with those of C. cinerea ( Figure 5C and Table S17) and H. sublateritium, respectively, and therefore might be responsible for the production of coprinoferrin-related compounds. Transcriptome analysis showed that all of the genes in the cluster were highly or moderately expressed.
Three indole clusters were found in the genome of S. rugosoannulata, far more than the majority of fungi that have no or only one indole cluster (Table S16). However, the three core genes (SRUG_09987, SRUG_10137, and SRUG_11196) had no or very low expression in the mycelial sample.

No Genes Encoding Psilocybin Biosynthesis Enzymes Were Predicted in the Genome of S. rugosoannulata
The species of the genera Conocybe, Gymnopilus, Panaeolus, Pluteus, Psilocybe, and Stropharia have been reported to be hallucinogenic mushrooms that contain psilocybin [47,48]. Among the species of the genus Stropharia, S. coronilla has been reported to produce psilocin/psilocybin [49], and no psilocin/psilocybin was detected in S. rugosoannulata by high-performance liquid chromatography (HPLC) analysis [50]. Enzymatic synthesis of psilocybin has been reported in the phylogenetically closed species P. cubensis and P. cyanescens [29]. We searched the genes encoding three key psilocybin biosynthesis enzymes, namely, tryptophan decarboxylase (PsiD), psilocybin-related N-methyltransferase (PsiM), and psilocybin-related phosphotransferase (PsiK), in the genome of S. rugosoannulata. It was found that the proteins SRUG_10179, SRUG_02421, and SRUG_10672 have only 38.5%, 27.5%, and 44.4% identity with the related enzymes responsible for psilocybin biosynthesis in P. cubensis, respectively. Phylogenetic analysis showed that the known psilocybin biosynthesis enzymes were grouped as a cluster with high support values, and the related proteins of S. rugosoannulata are grouped into different clusters with PsiD, PsiK, and PsiM, which were confirmed to encode for psilocybin biosynthesis enzymes ( Figure 6). This suggests that the gene cluster for psilocybin biosynthesis is absent in S. rugosoannulata, which is consistent with the result of no psilocin/psilocybin determined by HPLC [50]. rugosoannulata, which is consistent with the result of no psilocin/psilocybin determined HPLC [50].

Gene Encoding Cytochrome P450 in the Genome of S. rugosoannulata
Blastp analysis was performed against the Fungal Cytochrome P450 Datab (FCPD) and it was found that 217 cytochrome P450 monooxygenases in the

Gene Encoding Cytochrome P450 in the Genome of S. rugosoannulata
Blastp analysis was performed against the Fungal Cytochrome P450 Database (FCPD) and it was found that 217 cytochrome P450 monooxygenases in the S. rugosoannulata genome were classified into 57 families. The largest number was for CYP559 (26), followed by CYP65 (10) and CYP505 (9). Both CYP559 and CYP65 are involved in the secondary metabolism.

Discussion
In this study, we presented the genome sequence of S. rugosoannulata generated by Illumina and PacBio RSII long-read sequencing technologies. The monokaryotic strain used in this study was obtained from the cultivar CGMCC 5.2220, which is widely cultivated in China. We focused on analysis of the repertoire of PCWD enzymes, nutritional strategies, and secondary metabolite clusters. S. rugosoannulata was classified as LD with 100% probability by LDA analysis based on PCWD enzymes. The expansion of genes encoding lignin and xenobiotic degradation enzymes, cytochrome P450 involved in the xenobiotic metabolism, and siderophore clusters confirm the potential application for bioremediation. A nutritional strategy of LD will guide the substrate selection for fruiting body cultivation.
The assembly of N50 2.96 Mb and N90 1.35 Mb was significantly improved from the previously reported version of this species, which had an N50 of 8,626 bp [20] (Table S5). Since heterokaryotic stages are dominant during the lifecycle in the majority of basidiomycetes species, the monokaryotic strain helped obtain a high-quality genome. Currently, the high-quality genomes of some mushrooms, such as Gloeostereum incarnatum [52], Pleurotus tuoliensis [53], and Sanghuangporus sanghuang [54], have been sequenced and assembled with monokaryotic strains.
Peroxidases are a group of oxidoreductases that mediate the electron transfer from hydrogen peroxide (H 2 O 2 ) or organic peroxide to various electron acceptors. The results of sequence analysis indicated that the number of heme peroxidase-encoding genes (50) in the genome of S. rugosoannulata was twice the average of all of the tested fungi. The distinctive features are the much greater HTP (14), MnP (17), and APx-CcP (10) than the majority of the tested Agaricales.
As a critical contributor to the microbial ligninolytic system, MnP can oxidize Mn 2+ to oxidative Mn 3+ , which acts as a mediator for the oxidation of various phenolic compounds, as has been observed in the case of lignin or analogous structures such as xenobiotic compounds [55]. Atypical MnP has only one or two conserved acidic amino acid residues at the predicted Mn 2+ binding site and has been identified in some wood-degrading fungi [44]. All 17 MnPs in S. rugosoannulata are atypical. HTPs are peroxidases that mediate the oxidation of halides and other compounds, including N-dealkylation, sulfoxidation, epoxidation of alkenes, and benzylic hydroxylation [56]. APx-CcP is a functional hybrid between cytochrome c peroxidase and ascorbate peroxidase. All of these peroxidaseencoding genes in the genome of S. rugosoannulata contribute to its potential application in bioremediation.
Three functional groups of gene families encoding PCWD enzymes (cellulose, hemicellulose, pectin, and lignin/xenobiotic) in the genome of S. rugosoannulata were compared to LD, WR, and BR. The ratio of total lignin and xenobiotic-related genes (50.5%) was higher than that of WR (39.6%), BR (29.7%), and LD (41.1%, Table S12). The expansion of lignin-and xenobiotic-related genes in the genome of S. rugosoannulata is responsible for its potential application in bioremediation and its stronger ability to degrade lignin than most LDs.
S. rugosoannulata is found in forests or lawns on forest boards, fallen leaves, and rarely in decomposed wood [57]. Cultivation substrates include both cellulosic straw and lignin sawdust. Most studies have considered it an LD [9,16]; however, some reports have classified it as a WR [17,18]. It has been reported that LD fungi shares with WR fungi the plesiomorphic enzymatic network involved in cellulose decomposition, whereas genomic signatures related to hemicellulose-and lignin-degradation genes can separate LD fungi from most WR fungi [25]. The key differences are related to the absence of high-ligninolytic potential VP and LiP in most LD fungi compared to WR fungi. There were no VP or LiP genes in the genome of S. rugosoannulata (Table S11), which is similar to that observed in most LD fungi. However, the number of genes encoding manganese peroxidase (17) was considerably higher than the average in LD (4) and WR (12) fungi. Enzyme activity analysis has confirmed that manganese-oxidizing peroxidase is the predominant enzyme of lignin degradation during growth in beech wood microcosms of S. rugosoannulata [13]. Additionally, GH11 genes were found only in LD and a few wood decayers. The average number of GH11 genes was four in LD and one in WR; however, there was only one GH11 gene in S. rugosoannulata. It seems to be challenging to classify S. rugosoannulata into LD or WR. Therefore, the nutritional strategy of S. rugosoannulata was analyzed by LDA based on the 44 PCWD enzymes, and S. rugosoannulata was classified as an LD with 100% probability (Table S14).
The analyses of PCWD enzymes and nutritional strategy are important for substrate selection during fruiting body cultivation. For LD fungi such as Agaricus bisporus, composted cereal straw and animal manure are the key substrates for fruiting body cultivation [58]. However, sawdust is often used as one of the substrates and generally accounts for 30% of the medium for fruiting body cultivation of S. rugosoannulata in China. This is consistent with the expansion of genes encoding manganese peroxidase in the genome, which can help degrade lignin. On the contrary, as an LD fungus, S. rugosoannulata cannot grow well without cellulose. For example, when 100% sawdust was used to cultivate S. rugosoannulata, the spawn colonized on the substrates slowly, and there was almost no primordium differentiation or fruiting body formation (Figure 7), resulting in serious economic losses, whereas 100% bagasse fiber was good for fruiting body cultivation ( Figure 7). As an LD fungus, S. rugosoannulata has a significant impact on the carbon cycle in terrestrial ecosystems as a saprotrophic decayer of leaf litter and straw. plesiomorphic enzymatic network involved in cellulose decomposition, whereas genomic signatures related to hemicellulose-and lignin-degradation genes can separate LD fungi from most WR fungi [25]. The key differences are related to the absence of high-ligninolytic potential VP and LiP in most LD fungi compared to WR fungi. There were no VP or LiP genes in the genome of S. rugosoannulata (Table S11), which is similar to that observed in most LD fungi. However, the number of genes encoding manganese peroxidase (17) was considerably higher than the average in LD (4) and WR (12) fungi. Enzyme activity analysis has confirmed that manganese-oxidizing peroxidase is the predominant enzyme of lignin degradation during growth in beech wood microcosms of S. rugosoannulata [13]. Additionally, GH11 genes were found only in LD and a few wood decayers. The average number of GH11 genes was four in LD and one in WR; however, there was only one GH11 gene in S. rugosoannulata. It seems to be challenging to classify S. rugosoannulata into LD or WR. Therefore, the nutritional strategy of S. rugosoannulata was analyzed by LDA based on the 44 PCWD enzymes, and S. rugosoannulata was classified as an LD with 100% probability (Table S14). The analyses of PCWD enzymes and nutritional strategy are important for substrate selection during fruiting body cultivation. For LD fungi such as Agaricus bisporus, composted cereal straw and animal manure are the key substrates for fruiting body cultivation [58]. However, sawdust is often used as one of the substrates and generally accounts for 30% of the medium for fruiting body cultivation of S. rugosoannulata in China. This is consistent with the expansion of genes encoding manganese peroxidase in the genome, which can help degrade lignin. On the contrary, as an LD fungus, S. rugosoannulata cannot grow well without cellulose. For example, when 100% sawdust was used to cultivate S. rugosoannulata, the spawn colonized on the substrates slowly, and there was almost no primordium differentiation or fruiting body formation (Figure 7), resulting in serious economic losses, whereas 100% bagasse fiber was good for fruiting body cultivation ( Figure 7). As an LD fungus, S. rugosoannulata has a significant impact on the carbon cycle in terrestrial ecosystems as a saprotrophic decayer of leaf litter and straw. Siderophores are generally synthesized by two pathways: An NRPS-dependent pathway and an NRPS-independent pathway. It has been confirmed that CC1G_04210 (cpf1) Siderophores are generally synthesized by two pathways: An NRPS-dependent pathway and an NRPS-independent pathway. It has been confirmed that CC1G_04210 (cpf1) encodes a siderophore synthetase and this NPRS cluster is responsible for the production of coprinoferrin, which is necessary for extracellular iron acquisition and is crucial for the growth and maturation of C. cinerea [46]. Homologous comparison and transcriptome analysis revealed that the NRPS cluster (cluster 6 in Figure S9) in S. rugosoannulata might be responsible for the production of coprinoferrin-related compounds. These NPRS siderophore synthetases are widespread in mushrooms and evolved from a common ancestor of basidiomycetes [46]. Moreover, two other siderophore clusters (clusters 4 and 7 in Figure S9) were predicted by Antismash in the genome of S. rugosoannulata. Pfam analysis showed that the core genes SRUG_02402 and SRUG_04293 have pfam04183 (IucA/IucC family) and pfam06276 (ferric iron reductase FhuF-like transporter). IucA and IucC are members of a family of non-NPRS-independent siderophore synthetases which are involved in the production of siderophores [59]. These two core genes encoding for siderophores, namely, SRUG_02402 and SRUG_04293, are located on scaffolds 2 and 4 of the genome assembly of S. rugosoannulata, respectively, and two siderophore clusters were identified. However, the homologous genes of SRUG_02402 and SRUG_04293 in the other tested Agaricales mushrooms, such as H. sublateritium and C. cinerea, were adjacent and presented as a cluster ( Figure 5A,B). Siderophores can bind to various metals, including iron. In addition to their essential role in the growth of fungi, siderophores have shown their potential roles in bioremediation [60]. Gene recombination might occur, and two clusters for the NRPS-independent siderophore synthesis were formed. It seemed that S. rugosoannulata can produce more siderophores for iron acquisition.
Psilocybin, a serotonin receptor agonist that induces altered states of consciousness, can be produced by some Agaricales, such as Psilocybe cubensis, Gymnopilus dilepis, and Panaeolus cyanescens [61]. S. rugosoannulata has been widely cultivated in China and is recommended by the Food and Agriculture Organization as a cultivated mushroom for developing countries [2], implying safety. No psilocin/psilocybin was detected by HPLC analysis in S. rugosoannulata [50]. However, the genome data allowed us to make the first comprehensive inventory of the genes involved in psilocybin biosynthesis for comparison with known hallucinogenic mushrooms. Phylogenetic analysis revealed that the related proteins of S. rugosoannulata were grouped into different clusters compared to the known proteins responsible for psilocybin biosynthesis ( Figure 6). Consistent with safe usage as an edible mushroom, the S. rugosoannulata genome does not contain genes for known psilocin/psilocybin biosynthesis.

Conclusions
A high-quality genome of the S. rugosoannulata commercial cultivar in China was assembled, and the PCWD enzymes, nutritional strategy, and secondary metabolites were analyzed in this study. The expansion of genes encoding MnP, lignin and xenobiotic degradation enzymes, and cytochrome P450 involved in the xenobiotic metabolism in the genome of S. rugosoannulata can explain its strong ability to bioremediate and degrade lignin. Consistent with the fact that S. rugosoannulata is safe for use as an edible mushroom, the S. rugosoannulata genome does not contain genes for known psilocybin biosynthesis. Genome analysis of S. rugosoannulata will contribute greatly to fruiting body cultivation and will provide insight into its application in bioremediation.

Supplementary Materials:
The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jof8020162/s1, Figure S1: Statistical analysis for high-quality reads of the Stropharia rugosoannulata genome; Figure S2: Heterozygosity analysis based on Kmer analysis; Figure S3: The completeness evaluation of the assembled genome; Figure S4: GO enrichment of the predicted proteins in Stropharia rogosoannulata; Figure S5: KEGG classification of the predicted proteins in Stropharia rogosoannulata; Figure S6: Venn diagram of the orthologous gene families; Figure S7: Colinear comparison of the whole genomes of Stropharia rugosoannulata and Hypholoma sublateritium using MUMmer plots; Figure S8: Comparison analysis of the number of predicted proteins involved in the degradation of HE (hemicellulose), CE (cellulose), and L/X (lignin/xenobiotics); Figure S9: Biosynthetic gene clusters in the Stropharia rugosoannulata genome; Table S1: Sequencing data used for the genome assembly; Table S2: The genome information of the comparative analysis species; Table S3: The assembled results of the Stropharia rugosoannulata genome; Table S4: Summary statistics for telomere repeats in the assembly; Table S5: Genome information of SR68 and MG69; Table S6-1: Prediction results of the gene structure; Table S6-2: BUSCO prediction;  Table S6-3: Gene function annotation; Table S7: GO analysis of the secreted proteins; Table S8: Number of genes in a gene family; Table S9: Putative peroxidase-encoding genes of the 63 Agricomycotina [35]; Table S10: 17 MnP genes classification; Table S11: Putative peroxidase-encoding genes of Strophaira rugosoannulata; Table S12: The number of CAZyme families in 16 species; Table S13-1: Comparative analysis of the plant cell wall degradation (PCWD) gene families with 37 fungi-cellulose; Table S13-2: Comparative analysis of the PCWD degradation (PCWD) gene families with 37 fungi-hemicellulose; Table S13-3: Comparative analysis of the PCWD gene families with 37 fungi-lignin and xenobiotics; Table S14-1: Variables Failing Tolerance Test; Table S14-2: Classification function coefficients resulting from discriminant analysis obtained from PCWD characters; Table S14-3: Classification results; Table S15: The gene clusters of Strophatria rugosoannulata predicted by antiSMASH; Table S16: The number of gene clusters predicted by antiSMASH; Table S17: NRPS gene cluster responsible for coprinoferrin in Coprinopsis cinerea, Stropharia rugosoannulata, and Hypholoma sublateritium; Table S18: P450 genes involved in the xenobiotic metabolism of Stropaharia rugosoannulata.


An Odorant Receptor from the Proboscis of the Cotton Bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) Narrowly Tuned to Indole

Simple Summary Odorant receptors (ORs) are at the core of the high-efficiency and sensitive olfactory system in insects. The expression and specific function of ORs largely contribute to the habits and speciation of one species. Although being predominantly expressed in the antennae, ORs in non-olfactory organs are suggested to have particular roles in promoting the reproduction or host fitness of insects. Our previous work has identified four ORs in the mouthpart organs of Helicoverpa armigera. Here, we amplified the full-length sequences of HarmORs from the proboscis. Further functional characterization suggested that HarmOR30 narrowly tuned to indole, the vital nitrogen-containing compounds that mediate tritrophic interactions. Our study deepens the insight into the olfactory perception of H. armigera, and explored a candidate functional receptor target for studying the interaction between insects and their plant hosts. Abstract Helicoverpa armigera is a serious agricultural pest with polyphagous diets, widespread distribution, and causing severe damage. Among sixty-five candidate ORs in H. armigera, the co-receptor HarmOrco and three specific ORs with partial sequences were identified to be expressed in the proboscis by our previous work, whereas their exact function is not known yet. In this study, we first confirmed the expression of these ORs in the proboscis by full-length cloning, which obtained the complete coding region of HarmOrco, OR24, and OR30. We then performed functional identification of HarmOR24 and OR30 by co-expressing them respectively with HarmOrco in Xenopus oocytes eukaryotic expression system combined with two-electrode voltage-clamp physiology. By testing the response of HarmOR24/OR30-expressing oocytes against eighty structural-divergent compounds, respectively, HarmOR30 was characterized to narrowly tune to indole and showed a specific tuning spectrum compared to its ortholog in Spodoptera littoralis. As indole is a distinctive herbivore-induced plant volatile and floral scent component, HarmOR30 might play roles in foraging and mediating the interactions between H. armigera with its surrounding environment.

Introduction
As the dominant group of invertebrates in most terrestrial ecosystems of the world, insects perform vital ecological functions through their feeding activities in either mutualistic or antagonistic ways like pollination, decomposition, phytophagy, predation, and parasitism [1]. For accommodating various feeding niches, insects from different taxa have evolved diverse forms of feeding organs on the mouthparts [2,3]. In glossatan Lepidoptera, almost all the adults of moths and butterflies have a siphonate proboscis, an elongated feeding tube attached to the head, and is tightly coiled up and stored under the heads during rest position or stretched while feeding [4,5]. In addition to the function in feeding, the proboscis is reported to have sensory functions such as chemoreception and mechanoreception [4]. The external surface of the proboscis is equipped with various types of sensilla associated with chemo-and/or mechanosensilla, which are thought to process gustatory or mechanical information during food intake [6]. It is worth pointing out that the proboscis, and other non-olfactory organs, also have been reported to possess olfactory sensing function, despite antennae being the primary olfactory organ for odorant detecting. In the Diptera Anopheles gambiae, the labellum of the proboscis was indicated to detect a small spectrum of human-related odorants [7]. In the Lepidoptera hawkmoth Manduca sexta, olfactory neurons were identified in the proboscis sensilla for sensing the floral scent benzyl acetone (BA) of wild tobacco [8].
In insects, the transmission of initial odorant signals is mainly mediated by ORs, which are expressed on the dendrite membrane of olfactory sensing neurons in the sensilla [9]. Insect ORs share similar seven-transmembrane domains with G protein-coupled receptors in vertebrates and nematodes but have an inverted topology with an intracellular Nterminus and an extracellular C-terminus [10]. Two sub-families of ORs have been identified in insects: (1) the ligand-specific ORs, which own lots of members in one species and their sequences are divergent within or between organisms, and (2) the co-receptors Orco, whose sequences are highly conserved among divergent insect orders. The co-receptors are not known to respond to any naturally occurring ligands. Ligand-specific ORs play roles by coexpressing with Orco to form heteromeric complexes as ligand-gated ion channels [11,12]. Characterization of the OR family in numerous species has largely taken our insight into the chemoreception of insects. Previous studies have reported the expression of candidate ORs in the proboscis of several lepidopteran species. Studies in Heliothis virescens have revealed the presence of candidate ORs in the proboscis by using tissue expression surveys [13]. Likewise, by performing transcriptomic sequencing on different tissues, transcripts of some ORs are also identified in proboscis and other tissues in several lepidopteran species such as Spodoptera littoralis and Mythimna separata, etc. [14,15].
Our previous works have identified sixty-five candidate ORs by transcriptomic sequencing in Helicoverpa armigera, a severe agricultural pest with herbivorous larvae and pollinated adults [16][17][18]. We have characterized the sensilla types of proboscis, which is equipped with nine subtypes of sensilla, including a wall-multiporous one that implies its olfactory sensing function [18]. By transcriptomic assays of the adult mouthpart organs (proboscis and labial palps), we identified the candidate chemosensory genes, including four ORs (HarmOrco, OR24, OR30, and OR58). In addition, the transcripts of these OR genes have been detected in the legs and antennae of both sexes [18]. Functional identification of forty-four HarmORs has been performed by screening the ligands of each OR against multiple odorant compounds, whereas no ligand of HarmOR24 or OR30 was identified [19]. We raise the question of what the function of these ORs is? Here, we focused on the proboscis and performed full-length sequence cloning of HarmORs, including co-receptor HarmOrco and three specific ORs HarmOR24, OR30, and OR58. By screening the ligands of each OR through heterologous expression in the Xenopus oocytes system combined with two-voltage clamp electrophysiology, we characterized the function of HarmOR30 for sensing indole. As one of the most important nitrogen-containing aromatic compounds, indole has been reported to play crucial ecological roles in manipulating tritrophic interactions [20,21]. The indole-sensing function of HarmOR30, which is expressed in non-olfactory organs, might mediate the host-plant recognition of H. armigera.

Insects
The H. armigera moths used in this study come from a laboratory colony, which has been bred for more than ten generations under laboratory conditions (16:8 h light: dark photoperiod, 27 • C ± 1 • C and 60-65% RH) at the Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China. Male pupae were kept separately from females before eclosion. The moths were fed on 10% honey water until they were used for experiments.

RNA Extraction, cDNA Synthesis, and HarmORs Cloning
The tissues of adults were carefully dissected from the 1-to 3-day-old moths of both sexes and then stored in liquid nitrogen immediately. The total RNA of proboscis was extracted following the manufacturer's instructions using TriZol reagent (Invitrogen, Carlsbad, CA, USA.). After extraction, the quality of RNA was assessed with a Nan-oDrop ND-2000 spectrophotometer (Thermo Fisher Scientifc, Waltham, MA, USA) and in a 1.2% agarose gel. The first-strand cDNA was synthesized from 1 µg of total RNA using an oligo-dT primer by TransScript ® One-Step gDNA (TransGen Biotech, Beijing, China) and following the manufacturer's protocol. The product was either used directly for full-length cloning of HarmORs or stored at −70 • C.
For the full-length cloning of HarmORs, the coding region of each OR (HarmOrco, OR24, OR30, and OR58) was amplified by using PrimeSTAR HS DNA polymerase (Takara, Dalian, China) from the cDNA mixture (1:1) of the proboscis of both sexes by PCR using specific primers (Table 1)

Heterologous Expression of HarmORs: cRNA Synthesis and Oocyte Microinjection
The coding region of each HarmOR24 and OR30 was subcloned into eukaryotic expression vector pT7TS by using ClonExpressII One Step Cloning Kit (Vazyme Biotech Co., Ltd., Nanjing, China). The specific primers bearing a Kozak consensus of each OR are listed in Table 1. cRNAs of HarmOR24, OR30, and the co-receptor HarmOrco were generated from linearized expression vectors by using the mMESSAGE mMACHINE T7 kit (Ambion, Austin, TX, USA) according to the manufacturer's instructions. The expression vector of HarmOrco, which has been constructed in previous work [19], was used in this study. Then, the cRNA mixture of ORx/Orco (27.6 ng each) was injected (Nanoliter 2010, WPI Inc., Sarasota, FL) into single mature and healthy Xenopus oocytes (stage V-VII), which were dissected from female Xenopus laevis freshly and then treated with 2 mg/mL collagenase solution in 1 × Ringer's buffer (2 mM KCl, 96 mM NaCl, 5 mM HEPES pH 7.6, and 5 mM MgCl2) at room temperature for 40 min to 1 h. After injection, oocytes were incubated with 1 × Ringer's buffer, which was supplemented with 5% dialyzed horse serum, 50 mg/mL tetracycline, 100 mg/mL streptomycin, and 550 mg/mL sodium pyruvate, for 3-4 days at 18 • C.

Plant Volatile Compounds for Ligand Screening of HarmORs
Total eighty diverse volatile compounds (Supplementary Table S1), including shortand mid-chain carboxylic acids, amines, aldehydes, aromatics, terpenes, short-chain fatty acid derivatives, and nitrogen-containing heterocyclic compounds, were tested in this study. Stock solution (1 M) of each compound was prepared in dimethyl sulfoxide (DMSO) and stored at −20 • C. When performing ligands screening, each odorant was freshly prepared by diluting into the dosage of 10 −4 M with 1 × Ringer's buffer containing 0.8 mM CaCl 2 .

Whole-Cell Two-Electrode Voltage-Clamp Physiological Recording
The whole-cell current of a single oocyte to multiple plant odorants was recorded by OC-725C oocyte clamp (Warner Instruments, LLC, Holliston, MA, USA) at a holding potential of −80 mV. After the current return to baseline, each oocyte was exposed to each compound by rinsing with 1 × Ringer's buffer containing 0.8 mM CaCl 2 . The data were acquired by Digidata 1440A and analyzed by pCLAMP 10.2 software (Axon Instruments Inc., Union City, CA, USA). Each compound was tested with 4-7 single cells to confirm the response profile. The tuning spectrum of OR was generated and analyzed by using GraphPad Prism 5 (GraphPad Software Inc., San Diego, CA, USA).

Phylogenetic Analysis of Lepidopteran ORs
The phylogenetic tree of 312 ORs from six lepidopteran species was constructed based on the maximum-likelihood method. Sequences alignment of the amino acid was performed using MAFFT (10 December 2021, https://www.ebi.ac.uk/Tools/msa/mafft/). The tree was constructed using RAxML version 8 with the Jones-Taylor-Thornton amino acid substitution model (JTT) and 1000 bootstrap replicates to assess node support.

Full-Length Cloning of HarmOR Genes from the Proboscis
Our previous studies have identified four ORs in the proboscis, including the odorant co-receptor Orco with a complete open reading frame (ORF) and three partial sequences of HarmOR24, OR30, and OR58 [18]. To confirm the expression of these OR genes, we performed full-length cDNA cloning from proboscis based on reported sequences. The full-length of HarmOrco, OR24, and OR30, which encode a polypeptide of 400, 391, and 382 amino acid residues, respectively, were obtained successfully. We failed to clone the full-length sequence of HarmOR58, as no PCR product was obtained by using the specific primers. The possible reason might be the shallow expression quantity of this gene in the proboscis. The sequence of each OR gene is highly consistent with its reported sequence. The amino acid sequence of HarmOR24, OR30, and Orco shares 99.5%, 97.4%, and 100% identities with the reported reference sequence, respectively. The sequences of HarmOR24 and OR30 are shown in Supplementary Table S2. Transmembrane (TM) domains' prediction of each OR indicated that they have a typical seven TM domains and extracellular C-terminus.

Functional Identification of HarmORs
In H. armigera, the function of forty-four HarmORs expressed in adult antennae has been screened against a panel of sixty-seven plant volatiles in our previous studies, where no ligand of OR24 and OR30 was characterized [19]. Considering the particular expressing pattern of these ORs, we suppose that they may respond to ecologically relevant compounds and then perform further functional identification in vitro. We first subcloned them into the eukaryotic expression vector to generate the cRNA of each OR, respectively. Then, the cRNA mixture of HarmORx/Orco was injected into Xenopus oocytes followed by a whole-cell two-electrode voltage-clamp physiological system. Each cell was tested against eighty plant volatile compounds from diverse categories, including short-and mid-chain carboxylic acids, amines, aldehydes, aromatics, terpenes, short-chain fatty acid derivatives, and nitrogen-containing heterocyclic compounds. The result showed that HarmOR30 specifically tuned to indole, rather than its analogues 3-methylindole, indole-3carboxaldehyde, or any other structural-divergent compounds (Figure 1).

Functional Comparison of the HarmOR30 Orthologs
In Lepidoptera, functional identification of OR family has been systematically conducted in another noctuid moth S. littoralis by previous work, in which the tuning spectra of twenty-one SlitORs were screened against a panel of fifty-one volatiles [22]. By our previous phylogenetic studies, SlitOR32 was suggested to be the ortholog of HarmOR30 [19]. Here, we produced a coincident result by building a phylogenetic tree of 312 ORs

Functional Comparison of the HarmOR30 Orthologs
In Lepidoptera, functional identification of OR family has been systematically conducted in another noctuid moth S. littoralis by previous work, in which the tuning spectra of twenty-one SlitORs were screened against a panel of fifty-one volatiles [22]. By our previous phylogenetic studies, SlitOR32 was suggested to be the ortholog of HarmOR30 [19]. Here, we produced a coincident result by building a phylogenetic tree of 312 ORs from six lepidopteran species. The HarmOR30 orthologous clade, which contains one OR from each species of H. armigera, S. littoralis, Ostrina furnacalis, H. assulta, and two ORs from Bombyx mori, was identified with high node support based on bootstrap values (Figure 2). By comparing the tuning spectra of HarmOR30 and SlitOR32, we found the functional difference between the two orthologs, which share 85.9% amino acid sequence identity ( Figure 3). SlitOR32 has been reported to be mainly activated by three aromatic compounds benzyl alcohol, benzaldehyde, and indole [22], whereas HarmOR30 narrowly tuned to indole and failed to respond to neither benzyl alcohol nor benzaldehyde.

Discussion
In this study, we obtained the complete coding region of three HarmORs from the proboscis of H. armigera, and characterized the function of HarmOR30 for sensing indole. Indole is the most widely distributed member of nitrogen-containing compounds in nature across different kingdoms and has been reported to mediate interactions among intra/inter-species of plants, microbes, invertebrates, and vertebrates [23][24][25]. In planta, indole is a derivative of shikimate pathway, resulting in biosynthesis of the essential amino

Discussion
In this study, we obtained the complete coding region of three HarmORs from the proboscis of H. armigera, and characterized the function of HarmOR30 for sensing indole. Indole is the most widely distributed member of nitrogen-containing compounds in nature across different kingdoms and has been reported to mediate interactions among in-

Discussion
In this study, we obtained the complete coding region of three HarmORs from the proboscis of H. armigera, and characterized the function of HarmOR30 for sensing indole. Indole is the most widely distributed member of nitrogen-containing compounds in nature across different kingdoms and has been reported to mediate interactions among intra/interspecies of plants, microbes, invertebrates, and vertebrates [23][24][25]. In planta, indole is a derivative of shikimate pathway, resulting in biosynthesis of the essential amino acid tryptophan, a significant precursor for multifunctional and vital indole-containing secondary metabolites, such as indole-3-acetic acid (auxin), indole glucosinolates, etc. [24,[26][27][28]. In addition, it can be produced as an intermediate in the biosynthesis of benzoxazinoids, a class of non-volatile defensive compounds in grasses and maize that are effective against insects and plant pathogens [24,[29][30][31]. Indole can also be released as a volatile by the indole-3-glycerol phosphate lyase BX1 [32].
In maize and rice plants, indole is a specifically released herbivore-induced volatile in responding to the herbivorous attack [33][34][35]. Indole has been reported to be an essential factor in manipulating tritrophic interactions among host plants, herbivores, and its parasitoids [24,35,36]. It has been documented to be a general negative factor to the generalist herbivore S. littoralis, whose caterpillars and adults consistently avoid indole-producing plants for feeding or oviposition, and indole directly increases the mortality of caterpillars and reduces plant damage, despite the exposure to indole increased caterpillar growth [37]. On the other hand, certain natural enemy wasps against S. exigua and S. littoralis exploit indole to locate hosts for oviposition [35,38], whereas the story between caterpillars and wasps mediating by indole is not always reliable, as mentioned above. It was reported that tritrophic interactions can be undermined by indole, which reduces the suitability and attractiveness of caterpillars to parasitoids [38]. Within or between plants, indole was also documented as a fast and reliable priming signal to systemic tissues and neighboring plants at the early stage when there is a herbivorous attack [39,40]. It was suggested that indole is required for the priming of monoterpenes in systemic maize leaves, and enhances jasmonate-dependent defense and herbivore resistance in tea plants, likewise in other monocotyledonous and danzidicotyledonous plants [40][41][42][43].
Indole also acts as an anti-aphrodisiac to mediate the interaction between Pieris rapae and its parasitoid. Male P. rapae transfers a mixture of indole and methyl salicylate (MeS), which was generated by utilizing the amino acids tryptophan and phenylalanine as precursors, respectively, in P. rapae, to female at mating to curtail courtship and decrease the likelihood of female remating with conspecific males [44]. At the same time, the parasitic wasps of P. rapae have evolved relevant strategies by employing the anti-aphrodisiac mixture of indole and MeS to find their hosts [28,45]. It was reported that Trichogramma wasps were arrested after three days since P. rapae laid eggs on Brussels sprouts plants. Further studies showed that indole in the accessory reproductive gland secretion of mated female P. rapae induced changes in the foliar chemistry that arrested wasps [45]. Wasp species also exploit the anti-aphrodisiac mixture of indole and MeS of P. rapae by hitching a ride on a mated female butterfly, despite this behavior being innate in T. brassicae, whereas T. evanescens learns it after one successful ride on a mated female [28].
Floral scents are necessary signals mediating the interaction between plants and pollinators [46]. Indole is one of the most predominant components contributing to the floral fragrance in jasmine and tuberose [47,48] and is famous for its fragrant smell in low concentrations but the fecal smell in high concentrations. A case of indole is served as a scent signal to attract pollinators is that the wild hawkmoths Hyles lineata innately prefer the natural flowers of Ipomopsis tenuituba plants, which are light-pink and naturally emit indole and presented a stronger indole signal during the activity peak of hawkmoth [49,50]. It was demonstrated that indole attracts hawkmoths to flowers, although it has little effect on the rate at which the attracted moths probe flowers, and, combined with the high contrast (white color) of visual signals, together promote successful pollination [50].
As has been documented above, indole plays fundamental functions as a precursor, intermediate, or priming in the metabolism of organisms, as well as a crucial factor in manipulating tritrophic interactions. In H. armigera, HarmOR30 for sensing indole is expressed in non-olfactory organs including proboscis and legs, besides the olfactory organ antenna [18]. The particular expression pattern of HarmOR30 implies that it may play special functions in host plant evaluation. As mentioned above, maize plants specifically release indole after being attacked by herbivores such as S. littoralis. For H. armigera, maize is also hired as one of the most important host plants, the seedlings of which induce a large amount of indole when infested by H. armigera caterpillars [51]. HarmOR30 may be employed by the insect to detect the physiological state of plants: whether they are suffering an attack by other herbivores. On the other hand, as an essential floral scent compound in nearly thirty plant families, indole may also serve as a nectar clue for the adults of H. armigera, which generally bear pollen grains from a range of plant species during long-distance migration [23,52].
It is worth pointing out that HarmOR30 shows a more specific function to indole compared with its ortholog in S. littoralis. Despite being orthologs, their olfactory-processing function may finally lead to divergent behavior. In S. littoralis, no transcript of SlitOR32 was identified in other organs, including the proboscis, brain, and body except antennae [14]. On the other hand, a customized OR-expressing scheme for detecting ecological relevant cues might be employed by a specific organ in different insect species. For instance, different OR orthologs were reported to be expressed in the proboscis among three noctuid moths, respectively. In S. littoralis, SlitOR14 (the ortholog of HarmOR42), for sensing an aromatic floral scent phenylacetaldehyde, and SlitOR25 (the ortholog of HarmOR59), for mainly sensing acetophenone and benzyl alcohol, were identified by RT-PCR to show consistent expression patterns between both sexes [14,19,22]. However, in M. separata, MsepOR26 (the ortholog of HarmOR26, which mainly responds to terpene nerolidol) and MsepOR54 (the ortholog of HarmOR9) were identified by RT-PCR [15,19]. The differential expression of OR subset in proboscis may endow moths with diverse olfactory sensing functions while feeding, further promoting the differentiation of foraging preference among species.
Non-olfactory organs that are granted the odorant sensing function by specific OR have been reported by previous works. In the tobacco budworm H. assulta, HassOR31 is highly expressed in the female ovipositor, which thereby obtains the olfactory function for sensing (Z)-3-hexenyl butyrate, a volatile compound from host plants. It was suggested that gravid female moths take advantage of the odorant to find precise oviposition sites [53]. The hawkmoth M. sexta is a major pollinator of the wild tobacco Nicotiana attenuata, the flowers of which emit relatively simple floral volatile components dominated by BA [54]. The adults of M. sexta have coevolved a matched proboscis and exhibit an innate foraging preference to BA [3,55,56]. It was demonstrated that BA is detected only by proboscis, which is equipped with olfactory sensing neurons that express certain OR (not known yet) for detecting BA, and encourage the moth to visit a flower long enough for successful pollination [8]. The hawkmoth foraging with its slender proboscis inserts into the long corolla tube of N. attenuate 'on the wing', which costs particularly high energy [57]. Perceiving the flower scent only with the proboscis enables the moth to evaluate the specific quality of individual flowers at a very close range and significantly contributes to the moth's net-energy gain [3,8]. However, for the cotton bollworm moth, which uptakes nectar or liquid by landing on the surface of food sources, it seems to be unnecessary to evolve a dedicated olfactory line on the proboscis. Instead, they might utilize the olfactory function of proboscis in an auxiliary form combined with the antennae.
The physiological function and behavioral effect of indole on H. armigera have not been reported yet. Further behavioral assays combined with functional studies in vivo of HarmOR30 should be performed in our subsequent studies, aiming to investigate the efforts of indole on development, as well as the roles of indole in host-plant recognization and assessment. In addition, it is worth getting insights into these questions: (1) What is the significance of an insect expressing the same olfactory receptor in multiple organs?
(2) Does the olfactory signal of a specific odor from different organs contribute to the same physiological behavior? and (3) How does the olfactory signal from different sources get processed and integrated? Addressing these issues will contribute to our understanding of how an insect species interacts with its surrounding environment by employing specific olfactory strategies.